granulo loader program is cleaned from useless commented lines and useless print
brahim
parent
5d16adc521
commit
329639e064
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@ -1,7 +1,5 @@
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import matplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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import pandas as pd
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import pandas as pd
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from Model.GrainSizeTools import demodul_granulo, mix_gaussian_model
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class GranuloLoader:
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class GranuloLoader:
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@ -16,8 +14,7 @@ class GranuloLoader:
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self._y = self._data.iloc[:, 1].tolist() # distance from left bank (m)
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self._y = self._data.iloc[:, 1].tolist() # distance from left bank (m)
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self._z = self._data.iloc[:, 2].tolist() # depth (m)
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self._z = self._data.iloc[:, 2].tolist() # depth (m)
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self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2
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self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2 # grain radius (m)
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# self._r_grain = 1e-6 * np.array(self._data.columns.values)[5:].astype(float) / 2 # grain radius (m)
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self._Ctot = self._data.iloc[:, 3].tolist() # Total concentration (g/L)
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self._Ctot = self._data.iloc[:, 3].tolist() # Total concentration (g/L)
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self._D50 = self._data.iloc[:, 4].tolist() # median diameter (um)
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self._D50 = self._data.iloc[:, 4].tolist() # median diameter (um)
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@ -25,147 +22,3 @@ class GranuloLoader:
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self._frac_vol_cumul = np.cumsum(self._frac_vol, axis=1) # Cumulated volume fraction (%)
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self._frac_vol_cumul = np.cumsum(self._frac_vol, axis=1) # Cumulated volume fraction (%)
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# print(type(self._frac_vol_cumul), self._frac_vol_cumul.shape, self._frac_vol_cumul)
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# # --- Load sand sediments data file ---
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# self.path_sand = path_sand
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# self._data_sand = pd.read_excel(self.path_sand, engine="odf", header=0)
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#
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# self._Ctot_sand = np.array(self._data_sand.iloc[:, 2]) # Total concentration (g/L)
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# self._D50_sand = np.array(self._data_sand.iloc[:, 3]) # median diameter (um)
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# self._frac_vol_sand = np.array(self._data_sand.iloc[:, 4:]) # Volume fraction (%)
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#
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# self._frac_vol_sand_cumul = np.cumsum(self._frac_vol_sand, axis=1) # Cumulated volume fraction (%)
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#
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# # --- Compute % of fine and % of sand sediment in total concentration ---
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#
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# self._Ctot_fine_per_cent = 100 * self._Ctot_fine / (self._Ctot_fine + self._Ctot_sand)
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# self._Ctot_sand_per_cent = 100 * self._Ctot_sand / (self._Ctot_fine + self._Ctot_sand)
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# ==============================================================================================================
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# ==============================================================================================================
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# N_sample = 0
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# #
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# fig, ax = plt.subplots(1, 2)
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# ax[0].plot(self._r_grain, self._frac_vol[N_sample, :], color="k", marker='.')
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# ax[0].set_xscale('log')
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# ax[0].set_xlabel('Radius ($\mu m$)')
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# ax[0].set_ylabel('Class size volume fraction')
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#
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# ax[1].plot([self._r_grain[i+1]-self._r_grain[i] for i in range(self._r_grain.shape[0]-1)], list(range(self._r_grain.shape[0]-1)), color="k", marker="x")
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# ax[1].set_xlabel('Ecart inter-class')
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# ax[1].set_ylabel('n° échantillon')
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#
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# plt.show()
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#
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# print(f"self._r_grain.shape : {self._r_grain.shape}")
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# print(f"self._r_grain : {self._r_grain}")
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# print(f"self._frac_vol_cumul.shape : {self._frac_vol_cumul[N_sample, :].shape}")
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# print(f"self._frac_vol_cumul[N_sample, :] : {self._frac_vol_cumul[N_sample, :]}")
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# print(np.where(self._frac_vol_cumul[N_sample, :] > 0))
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# #
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# min_demodul = 1e-6
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# max_demodul = 500e-6
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# sample_demodul = demodul_granulo(self._r_grain[:],
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# self._frac_vol_cumul[N_sample, :],
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# min_demodul, max_demodul)
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#
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# print(f"sample_demodul : {sample_demodul.demodul_data_list}")
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# N_modes = 3
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# sample_demodul.print_mode_data(N_modes)
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# sample_demodul.plot_interpolation()
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# sample_demodul.plot_modes(N_modes)
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#
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# print(f"mu_list : {sample_demodul.demodul_data_list[3 - 1].mu_list}")
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# print(f"sigma_list : {sample_demodul.demodul_data_list[3 - 1].sigma_list}")
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# print(f"w_list : {sample_demodul.demodul_data_list[3 - 1].w_list}")
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#
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# resampled_log_array = np.log(np.logspace(-10, -2, 3000))
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# proba_vol_demodul = mix_gaussian_model(resampled_log_array,
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# sample_demodul.demodul_data_list[2].mu_list,
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# sample_demodul.demodul_data_list[2].sigma_list,
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# sample_demodul.demodul_data_list[2].w_list)
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#
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#
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#
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# proba_vol_demodul = proba_vol_demodul / np.sum(proba_vol_demodul)
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# ss = np.sum(proba_vol_demodul / np.exp(resampled_log_array) ** 3)
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# proba_num = proba_vol_demodul / np.exp(resampled_log_array) ** 3 / ss
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#
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# print(f"proba_num : {proba_num}")
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# freq = 5e6
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#
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# a2f2pdf = 0
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# a3pdf = 0
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# for i in range(len(resampled_log_array)):
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# a = np.exp(resampled_log_array)[i]
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# a2f2pdf += a**2 * form_factor_function_MoateThorne2012(a, freq)**2 * proba_num[i]
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# a3pdf += a**3 * proba_num[i]
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#
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# print(f"a2f2pdf = {a2f2pdf}")
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# print(f"a3pdf = {a3pdf}")
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#
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# ks = (a2f2pdf / a3pdf)
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#
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# print(f"ks = {ks}")
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#
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#
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# def form_factor_function_MoateThorne2012(a_s, freq, C=1500):
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# """This function computes the form factor based on the equation of
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# Moate and Thorne (2012)"""
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# # computing the wave number
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# k = 2 * np.pi * freq / C
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# x = k * a_s
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# f = (x ** 2 * (1 - 0.25 * np.exp(-((x - 1.5) / 0.35) ** 2)) * (
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# 1 + 0.6 * np.exp(-((x - 2.9) / 1.15) ** 2))) / (
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# 42 + 28 * x ** 2)
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# return f
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# if __name__ == "__main__":
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# GranuloLoader("/home/bmoudjed/Documents/2 Data/Confluence_Rhône_Isere_2018/Granulo_data/fine_sample_file.ods")
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# GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/Granulo_data/"
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# "sand_sample_file.ods")
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# GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
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# "pt_acoused_cnr_7nov2023/echantil/fine_new_file_acoused_101RDS 3.ods")
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# GranuloLoader("/home/bmoudjed/Documents/3 SSC acoustic meas project/Graphical interface project/Data/"
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# "pt_acoused_cnr_7nov2023/echantil/sand_new_file_acoused_101RDS 3.ods")
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# # form_factor = form_factor_function_MoateThorne2012(GranuloLoader.)
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#
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# def ks(a_s, rho_s, freq, pdf):
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# # --- Calcul de la fonction de form ---
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# form_factor = form_factor_function_MoateThorne2012(a_s, freq)
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# print(f"form_factor shape = {len(form_factor)}")
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# # print(f"form_factor = {form_factor}")
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#
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# # --- Gaussian mixture ---
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# # sample_demodul = demodul_granulo(a_s.astype(float), pdf, 0.17e-6, 200e-6)
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# # sample_demodul.plot_interpolation()
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#
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# # ss = np.sum(pdf / a_s ** 3)
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# # proba_num = (pdf / a_s ** 3) / ss
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#
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# # --- Compute k_s by dividing two integrals ---
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# a2f2pdf = 0
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# a3pdf = 0
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# for i in range(len(pdf)):
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# a2f2pdf += a_s[i] ** 2 * form_factor[i] * proba_num[i]
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# a3pdf += a_s[i] ** 3 * proba_num[i]
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#
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# ks = np.sqrt(a2f2pdf / (rho_s * a3pdf))
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#
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# # ks = np.array([0.04452077, 0.11415143, 0.35533713, 2.47960051])
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# # ks = ks0[ind]
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# return ks
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